How robust are meta-analyses to publication bias? Sensitivity analysis methods and empirical findings

Publication bias can distort meta-analytic results, sometimes justifying considerable skepticism toward meta-analyses. This talk will discuss recently developed statistical sensitivity analyses for publication bias, which enable statements such as: “For publication bias to shift the observed point estimate to the null, ‘significant’ results would need to be at least 10-fold more likely to be published than negative or ‘non-significant’ results” or “no amount of publication bias could explain away the average effect.” The methods are based on inverse-probability weighted estimators and use r

The rational use of cognitive resources

Psychologists and computer scientists have very different views of the mind. Psychologists tell us that humans are error-prone, using simple heuristics that result in systematic biases. Computer scientists view human intelligence as aspirational, trying to capture it in artificial intelligence systems. How can we reconcile these two perspectives? In this talk, I will argue that we can do so by reconsidering how we think about rational action.

Curious, cooperative, and communicative: How we learn from others and help others learn

Humans are not the only species that learns from others, but only humans learn and communicate in rich, diverse social contexts, and build repertoires of abstract, structured knowledge. What makes human social learning so distinctive, powerful, and smart?  In this talk, I argue that social learning is inferential at its core (inferential social learning); rather than copying what others do or trusting what others say, humans learn from others by drawing rich inferences from others’ behaviors, and help others learn by generating evidence tailored to others’ goals and knowledge states.

The Implications of Polysemy for Theories of Word Learnin

Most common words in English and in other languages are polysemous, expressing a family of distinct but related meanings (e.g., “chicken” can refer to a kind of animal, meat, game, or cowardly person). Yet within developmental science, word learning is typically studied as a problem in which children need to learn one meaning for each word. I will argue that simplifying the object of study in this way has led researchers to formulate theories which incorrectly predict that children should struggle at learning polysemous words.

Using DNA to predict children's developmental differences

Children's differences in early life development have pervasive, long-term influence on their later life outcomes, such as education, health, and well-being. A major source of children's developmental differences is their family background, which includes the rearing environments that they grow up in and the DNA differences that children inherit from their parents.

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